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i-timur
/
microdata-classifier

Text Classification
Transformers
Safetensors
bert
text-embeddings-inference
Model card Files Files and versions
xet
Community

Instructions to use i-timur/microdata-classifier with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use i-timur/microdata-classifier with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("text-classification", model="i-timur/microdata-classifier")
    # Load model directly
    from transformers import AutoTokenizer, AutoModelForSequenceClassification
    
    tokenizer = AutoTokenizer.from_pretrained("i-timur/microdata-classifier")
    model = AutoModelForSequenceClassification.from_pretrained("i-timur/microdata-classifier")
  • Notebooks
  • Google Colab
  • Kaggle
microdata-classifier
715 MB
Ctrl+K
Ctrl+K
  • 1 contributor
History: 5 commits
i-timur's picture
i-timur
chore: fine-tune model on data from 5000 to 10000
d38d5d4 about 2 years ago
  • .gitattributes
    1.52 kB
    initial commit about 2 years ago
  • .gitignore
    10 Bytes
    env: add .gitignore about 2 years ago
  • config.json
    1.24 kB
    chore: fine-tune model on data from 2500 to 5000 about 2 years ago
  • model.safetensors
    711 MB
    xet
    chore: fine-tune model on data from 5000 to 10000 about 2 years ago
  • special_tokens_map.json
    695 Bytes
    chore: fine-tune model on data from 2500 to 5000 about 2 years ago
  • tokenizer.json
    2.92 MB
    feat: add microdata classifier about 2 years ago
  • tokenizer_config.json
    1.3 kB
    chore: fine-tune model on data from 2500 to 5000 about 2 years ago
  • vocab.txt
    996 kB
    feat: add microdata classifier about 2 years ago